Cost-Effectiveness of Pembrolizumab Versus Carboplatin and Paclitaxel in Patients With Unresectable or Metastatic Melanoma After First-Line Treatment in China



This study aimed to evaluate the cost-effectiveness of pembrolizumab compared with standard-of-care chemotherapy (paclitaxel + carboplatin [PC]) in patients with unresectable or metastatic melanoma after first-line treatment from a Chinese healthcare system perspective.


We conducted a partitioned-survival model with a 1-week cycle length and a 20-year base-case time horizon. Piecewise parametric models were fitted to KEYNOTE-006 trial data to estimate progression-free survival and overall survival for pembrolizumab, and a network meta-analysis was used to estimate the clinical outcomes for standard of care. Quality-adjusted life-years (QALYs) were calculated using EQ-5D data from KEYNOTE-006, applying Chinese-specific utility tariffs. Costs included drug acquisition, administration, adverse events, and disease management, reflecting the Chinese pricing system. Chinese-specific disease management costs were estimated based on clinical opinion on health state resource use and chemotherapy-related adverse events. Costs and outcomes were discounted at 5% annually. Multiple deterministic and probabilistic sensitivity analyses were performed to test the robustness of the results.


In the base-case analysis, the treatment of pembrolizumab is estimated to yield 2.63 life-years (LYs) and 2.24 QALYs at an incremental cost of ¥372 316.46 versus PC. The incremental costs per LY and per QALY were ¥141 771.00 and ¥165 865.69, respectively, the latter being below a threshold of 3 times the per capita gross domestic product (¥193 932) in China, deemed as cost-effective according to the World Health Organization threshold. These findings were robust against a wide range of sensitivity analyses.


Pembrolizumab is projected as cost-effective compared with PC in patients with unresectable or metastatic melanoma after first-line treatment in China.


Wen-xi Tang Rong-jie Shao Jingshu Wang Emilie Scherrer Ai-xia Ma Raquel Aguiar-Ibáñez

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